Fish diversity and biomass in northern Canadian lakes: northern lakes are more diverse and have greater biomass than expected based on species–energy theory
Bibliographic record
Abstract
Biodiversity in northern Canada (north of 60°N latitude) is threatened, primarily by increasing resource exploitation and by climate change. Unfortunately, we have relatively limited knowledge of aquatic biodiversity for this region, making it difficult to develop suitable policies to manage these threats. Here we describe, quantify, and test hypotheses related to fish biodiversity and biomass in 37 lakes in a diamond mining district (the Barrenlands) in the Northwest Territories, Canada (64°N, 110°W). To estimate species richness and biomass of fish, we took advantage of exhaustive sampling and monitoring surveys conducted in the region and compared our northern estimates against estimates from southern Canadian lakes. We found that most of the 37 northern lakes contained two to four species, with the largest lake containing eight species. Salmonids dominated this system, with lake trout (Salvelinus namaycush) being the dominant species in abundance and biomass. Comparative analysis with similar-sized southern Canadian lakes showed no significant difference in the slopes of species richness versus lake area curves. Surprisingly, total fish biomass distributions for northern, Barrenlands lakes were also similar to southern, Ontario lakes. Overall, our results suggest that Barrenlands lakes are important natural resources of Canada that should be conserved for the future. Under anticipated scenarios of climate change, these lakes may represent important refugia for coldwater fishes (e.g., lake trout) as habitats at the southern edges of their ranges become more limiting.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".